Mobile communications networks are in the process of offering increasingly sophisticated capabilities associated with the motion and/or position location sensing of a mobile device. New software applications, such as, for example, those related to personal productivity, collaborative communications, social networking, and/or data acquisition, may utilize motion and/or position sensors to provide new features and services to consumers. Moreover, some regulatory requirements of various jurisdictions may require a network operator to report the location of a mobile device when the mobile device places a call to an emergency service, such as a 911 call in the United States.
In conventional digital cellular networks, position location capability can be provided by Advanced Forward Link Trilateration (AFLT). AFLT may compute the position of a wireless device from the wireless device's measured time of arrival of radio signals transmitted from a plurality of base stations. Improvements to AFLT have been realized by utilizing hybrid position location techniques, where the mobile station may employ a Satellite Positioning System (SPS) receiver. The SPS receiver may provide position information independent of the information derived from the signals transmitted by the base stations. Moreover, position accuracy can be improved by combining measurements derived from both SPS and AFLT systems using conventional techniques. Additionally, with the increased proliferation of micro electro-mechanical systems (MEMS), small, on-board sensors may be used to provide additional relative position, velocity, acceleration and/or orientation information.
Position location techniques based upon signals provided by SPS and/or cellular base stations may encounter difficulties when the mobile device is operating within a building and/or within urban environments. In such situations, multipath and/or degraded signal strength can significantly reduce position accuracy, and can slow the “time-to-fix” to unacceptably long time periods. These shortcomings may be overcome by exploiting signals used in existing wireless data networks, such as Wi-Fi (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.11x standards), and having elements within the network infrastructure derive position information of the mobile device.
Having the network infrastructure accurately determine the position of a mobile device, utilizing signals from existing wireless data networks, may involve knowledge of precise time delays incurred by the wireless signals due to the latency of the mobile device and/or other network elements. Such delays may be spatially variant due to, for example, multipath and/or signal interference. Moreover, such delays may change over time based upon the type of network device and/or the network device's current networking load. Also, having the network determine position accurately using conventional techniques may involve precise time synchronization of elements within the network which may be difficult in practice to accomplish and maintain.
Thus, a need exists for a network centric position determination approach which can estimate processing delays and not require precise time synchronization of networking elements.